The Connection Between Health and Economic Growth: Policy Implications Re-examined

The Connection Between Health and Economic Growth: Policy Implications Re-examined

DAVID ODRAKIEWICZ

M.A. Economics University of Aberdeen, Researcher GPMI Director of International Relations

Abstract: In order for governments to implement important policies for better health and enhanced economic growth, it is vital to first consider both the processes and connections that trigger the complicated relationship between health and income. For many years the causality running from income to health has been recognized as a principal and instinctual proposition. However, recent literature presents empirical evidence of a reversed causation – from health to income. This paper focuses on the reversed causation by analyzing three recent case studies that use panel data, providing a multi-dimensional perspective, and thus enabling the findings to form general solutions to policy problemsthat governments face worldwide. Bloom and Canning (2001) argue that both directions of causality can work together at the same time. This leads to a virtuous circle where health enhancements stimulate economic growth, which then stimulates health. Taking into account a scenario where both variables stimulate one another leads to significant policy implications. Drawing on evidence provided in this paper, policymakers should look at health expenses as an investment rather than a cost, taking a balanced approach, and implementing a long run viewpoint. Governments must take health seriously if they want sustain and improve on economic and social outcomes.

Academic literature indicates a possible two-way relationship between health and GDP. The effect of economic growth on the population’s health is more straightforward and easier to explain. As income lev- els rise so does the level of health expenditure, as it is a function of income. Martin et al. (2008) proved increased health expenditure on average leads to im- provements in health. Moreover, wealthier individu- als tend to spend a larger fraction of their disposable income on better quality nutrition, hence, positively impacting their health status – Bloom, Canning (2008). Examining the reverse causation from health to GDP becomes more complicated and evidence is mixed. Theoretically, health is a determinant of human capital and labour productivity. Consequently, health expen- ditures as investments in health should result in higher income levels. Treating health as an investment good is exceptionally important for governments, allowing them to carry out cheap and easily implementable health policies that can improve health dramatically, even in the poorest countries. However, many studies come across the problem of endogeneity when exam- ining the relationship, which makes estimations very inaccurate and unreliable. Another problem occurs due to the problematic measurement of health: separate studies use different indicators of health, making it hard to compare their findings.

The main aim of this paper is to analyze the exis- tence of this two-way relationship and examine policy implications that impose critical economic conse- quences. Since the direction of causality from eco- nomic growth to health has been extensively studied and decisively proven, this work will placeemphasis on the reversed causality. It is important to study the significance of health on long-term economic growth, particularly in times of recession, as health may play a major part in government’s decisions to rescue their economies. Health improvements are not only problems that developing countries face, but also de- veloped nations need to be concerned with sustaining good health status and putting across health policies that increase the efficiency of the provision of health. This study will try to validate the existence of the re- versed causality and recommend policies enhancing economic growth.

LITERATURE REVIEW

Over the past century both health status and the world’s gross domestic product have risen continu- ously to new record levels. There has been extensive academic research to understand the relationship between them. Theoretical literature shows that there might exist a casual relationship between health and GDP, which runs in both directions, since the empiri- cal evidence is mixed.A study by Devlin and Hansen (2001) looked at the Granger causality between health expenditure and GDP and discovered that undeniably there may be a two-way (Granger) causality between health spending and income. It is important to point out the possible presence of an intermediate factor – education, which can independently have an effect on both income and health. Bloom and Canning (2000) explained the direction of the causality with education as an intermediate factor, finding that healthy individu- als tend to live longer and have motivation to invest in their abilities, hence increasing their human capital value. This in turn has positive side effects on income. Theyunderpinned their findings with Smith’s (1999) life cycle model, which connected health status with future income, welfare and consumption. Erdil and Yetkiner (2004) examined causality between GDP and health spending among countries that possesseddiverse income levels throughout the years 1990-2000. The re- sults were very interesting as they were completely op- posite when low- and moderate-income countries were compared to high-income countries. When observing the low- to moderate-income countries, the causality ran from income to health expenditures, while in the high-income countries health spending had an effect on GDP. Luft (1978, p. 15) described the causality in an informal way: “ many people who would otherwise not be poor are poor simply because they are sick, but relatively few people who would otherwise be healthy are sick simply because they are poor”.

WEALTHIER IS HEALTHIER

Preston (1975) depicted by graph the relationship betweengrowth (national income per head) and health (life expectancy) in the 1930s and in the 1960s, finding a curvilinear association. The correlation coefficient between the logarithm of national income and life expectancy in 1930s was 0.885 and in the 1960s 0.880. Deaton (2003) updated the Preston curve in 2000.

In an article “Wealthier is Healthier” –Pritchett and Summers (1996) discovered that there is also a relationship between income and infant mortality, proving that 40% of infant mortality improvements can be explained bya country’s growth rates. Cutler et al. (2006) basing his findings on work by McKe- own (1976) revealed that before the introduction of contemporary medicine, British mortality rates had finished most of their historical decline. It is important to point out that the reasons behind this substantial fall are problematic and extensively debated. There are many possible causes, including: upgrades in liv- ing standards, enriched nutrition, and wide-ranging Victorian public health reforms. However, Cutler et al. explains that the fall in mortality rates was mainly due to the rise in income over this period of time. Wilkin- son (1996) studied how income inequality within a country transmutes into health gradients. Establishing his discoveries from U.S. Caucasian men in 1980, he concluded there exists a strong relationship between age-adjusted mortality and different income groups. Hence, his findings supported the theory that there is a link between income and health, which occurs between countries, within countries and over time.

In addition to Pritchett and Summers (1996) previous findings, they also found evidence that the relationship between health and income is not only correlational but causal as well. Even when holding all other viable variables constant, they noticed a sta- tistically meaningful influence of income on health. Furthermore, they found that factors that determine growth, but not health, such as global terms of trade, also are indirectly correlated to infant mortality. The fact that causal variables, which determine income, also have an impact on infant mortality supports their conclusions that the causation moves from income to health. This has been backed up by Ingram’s (1992) earlier experiment, which displayed that GDP per capita is associated with both health inputs of doctors per capita and daily calorie intake. Even though Pres- ton’s curve from 1975 clearly showed the relationship between income and health, Preston himself noticed that the curve shifts upwards over time. This led to a discussion about what really influences the rise in health over time. Preston (1975), Wilkinson 1996) and Cutler et al. (2006) all came to the same conclusions, suggesting that income is not the only factor shaping the world’s health status, but improvements in public health, health knowledge, and health technology also play an important role in health status. Javadipour and Mojtahed (2005) acknowledged income as being the most crucial variable in determining health status and found a strong correlation between low income and hygienic poverty. As a society’s financial status weakens, this tends to lead to an increased rate of dis- ease and mortality. When using mortality, diseases and exploitation of health services as criteria to assess the society’s health status, a reverse relationship between poor health and GDP of a society holds. Moreover, they argue that an individual must possess a certain sufficient amount of income in order to access other variables, which influence health, such as housing, nutrition and education. Hence, this underlines the great importance of income when looking at health- status related problems.

HEALTHIER IS WEALTHIER

Rice et al. (1990) examined the detrimental effect of mental disorders on the US economy, estimating the total cost to be equal to 148 billion dollars. This was mainly caused by fall in employment, a 14% reduction for the women and 12.5% for men.A study carried out by Fogel (1994) found that 30% of economic growth experienced by the British society in the last two hundred years could be attributed to improvements in nutrition. Fogel interprets nutrition as being an essential variable that has a positive influence on labour force participation. Arguing further that improved health not only reduces the number of sick days, but also improves the quality of work supplied by a given amount of labour, Barro (1997) projected that a 10% jump in life expectancy leads to a 0.4% increase in economic growth. Bloom and Malaney (1998), while examining 78 countries during the period 1965-1990 suggested that the mortality crisis, which occurred in Russia in the first half of 1990’s led to a fall in life expectancy from 70 to 65 consequently lowered the countries GDP by an estimated 1.8 to 2.7%. Rivera and Currais (1999a,b),using health expenditures per capita as their main indicator for measuring a population’s health, found that countries which possessed higher health expenditures had higher economic growth. They studied this relationship for OECD countries over the period of 1960-1990. Furthermore, when treating investment in health as a descriptive variable for output, they discovered that education is not the only element which promotes labour productivity and performance. Nordhaus (1999) proclaims that health improvements over the twentieth century have had the same positive impact on the economy as all the non-health benefits put together. Bloom and Canning (2000) researched developing countries, trying to analyze the relationship between health and income, basing their findings on four different channels through which health influences productivity:

• Individuals with greater health not only have less sick days, but are also more mentally and physically prepared for work.

• Individuals who live longer have a greater incentive to invest in education and acquire higher return on such investments.

• The level of savings increases as the individual’s life expectancy rises, hence stimulating investment.

• Better health in the form of higher life expectancy and improved child health may lead to a decrease in the impregnation rate, hence adults participate more extensively in the labour market, allowing them to obtain higher income per capita.

They found that countries which exhibited an increased life expectancy of five years enhanced their growth rate of real income per capita by approximately 0.3-0.5%. The WHO’s Commission on Macroeconomics and Health (2001) in their report underlined the great importance of expanding the coverage of vital services for countries struggling with sustainable development. This would save millions of lives each year, decrease poverty, increase economic growth and endorse worldwide security. They estimated that aiding the selected countries would cost $66 billion, which would in the long run increase economic output by $186 billion per year and save approximately 8 million lives.Dixon et al. (2001) reviewed the influence of life expectancy and epidemic diseases on economic growth, examining 104 countries over the period 1980-1992. Their general conclusion showed the positive association of life expectancy and negative connection of epidemic diseases with economic growth. Bloom et al. (2001) studied the impact of life expectancy on economic growth. They all came to the conclusion that health has a positive influence on growth and that just one year of increased life expectancy in the population leads to a 4% increase in national production.Heshmati (2001) used the generalized Solow growth model to examine the relationship between health spending and GDP. Health expenditure was plugged into the growth function as the variable representing health status. The summary of the findings showed that health expenditures had a positive and significant influence on GDP and that the presence of health spending decreases the importance of the impact of human capital on economic growth. Muysken, Yetkiner, and Ziesemer (2003) all agree that health expenditure can increase labour supply and productivity, ultimately leading to an increase in income. Chakraborty (2004) also came to the same conclusions as Bloom et al. (2001) when examining the correlation between life expectancy and GDP for 95 countries over the period 1970-1990. Cole and Neumayer (2005) used malnutrition, malaria and accessibility to healthy water as factors representing health status when examining the relationship between health and income. The study was done in 152 countries between the years 1965-1995 and showed a negative impact of all three factors on economic growth. Mojtahed and Javadipour (2004) researched the impact of health expenditures on economic growth in thirty-three developing countries between 1990- 1998 using the generalized Solow growth model, inter-country approach and panel data model. The study resulted in a positive and significant impact of health expenditure as a variable of health capital on economic growth. However, they also mentioned the importance that human capital has on economic growth contrary to Heshmati (2001).

The literature above provides clear evidence that the relationship between health and economic growth runs both ways. However, it important to point out that both relationships do not run separately, but mutually. Therefore, as health increases income, increased in- come positively affects health generating a virtuous circle.

HEALTH AND POLICY IMPLICATIONS

This section will focus on the significance of partial government market control and three aspects policymakers need to take into consideration before exercising any decisions: efficiency and effectiveness, equity, and sustainability. Morand (2005) explains how economic growth in the long run leads the soci- ety to live healthier and longer lives. The impact of income on health comes through two main channels. Firstly, as growth is enhanced so is per-capita income, which in turn provides the opportunity for individu- als to consume a higher quantity of superior nutrients needed to improve their health. Secondly, economic growth has its roots in technological change, with the improvements in technology helping to develop new medicine, and improved treatments aiding increased longevity. Morand suggests that the clear evidence describing how economic growth positively affects health has a direct policy implication. Case (2001) believes the provision of cash benefits is an important policy tool for governments concerned with enhancing the population’s health status.

Atun and Gurol-Uganci (2005) underline that any form of health expenditure should be considered as an investment, not a cost, in line with recent empirical evidence proving the positive impact health investment has on the economy and welfare of a country. They argue government intervention is required in order to avoid market failure of the health sector. However, the government should not overregulate the sector, slowing the progress of the sector. Instead, it should construct an environment under which there is an incentive for the investment in innovative technolo- gies. Governments can do this through various health- related policies that emphasize the long-run benefits, as short term policies usually focus on budget profits rater than economic and welfare benefits. Furthermore, it is very important to understand that improvements in health take time, and that evidence-based decision- making is crucial to enable the efficient exploitation of system resources available. They recommend that governments reorganize domestic health systems and improve allocative and technical efficiency. Atun (2004) claims a transfer from a hospital-intensive health system to a more community-based delivery system, which would increase the demand-pull factor via a larger participation of users, would enlarge the benefits for all key stakeholders. World Health Orga- nization (1999) also complies with the Atun and Gurol- Uganci (2005) findings and describes investment in health as an important macroeconomic policy tool.

Wilkie and Young (2009) point out three major ar- eas whichpolicymakers should consider when attempt- ing to improve health outcomes. First of all, efficiency and effectiveness of health expenditures prove to be as important as the quantity supplied. Jourmand et al. (2008) show that certain OECD countries still have an opportunity to increase their life expectancy figures without increasing their total health expenditure, but by improving their efficiency. Australia comes out as the most efficient OECD country in this study, where both the private and public sector provide health care. The measurement of the health spending efficiency and effectiveness can be problematic, however it is vital in defining and observing cost-effectiveness. Policymakers should compensate health providers who emphasise the quality and accessibility of their health services. Secondly, policymakers need to consider the impact of increased health spending on equity. Although many studies have shown that increased health expenditure tends to enhance the average health status of a population, it is hard to measure if the effect has been spread evenly across the society. Governments interested in equity goals should pay attention to specific groups of the society, ensuring that the targeted groups benefit from an increase in expenditure. Finally, the sustainability of health ex- penditures in the long run is a very important aspect policymakers need to take into consideration. Over the last twenty years no-demographic factors (e.g. new medical treatments) largely contributed to increases in health spending. Another factor that maintains health expenditure growth is community demand. As individuals’ disposable income increases they become more willing to cut their consumption on goods and services in favour of health-related products, which allow them to increase their life expectancy. This sec- tion concludes the theoretical part of this paper; the next chapter will present three separate case studies examining the effect of health on income.

THREE CASE STUDIES – ANALYSIS AND POLICY IMPLICATIONS

The literature on the relationship between health and economic growth clearly provides evidence for the existence of causality running both ways. How- ever, scholars generally agree the impact of economic growth on health is more recognizable. When examin- ing the reverse causality the evidence is mixed. There- fore, this section will focus on this reversed causality by analyzing three recent case studies separately, and in detail: two acknowledging the causality, and one providing no evidence of the existence of such a relationship. The case studies presented below have been specifically chosen as they alluse panel data, pro- viding a multi-dimensional perspective, enabling the findings to form general solutions to policy problems thatgovernments face worldwide.

THE RELATIONSHIP BETWEEN HEALTH AND GDP IN OECD COUNTRIES IN THE VERYLONG RUN – ROBIN SWIFT (2011)

Robin Swift (2011) examined the relationship be- tween health and GDP for 13 OECD countries over the last two centuries, using the Johansen multivariate cointegration analysis. Total GDP and GDP per capita data were gathered from Maddison (2003), while data on life expectancy at birth were collected from the Human Mortality Database. Figure 1 plots the cor- relation between life expectancy and GDP over time for England and Wales, which are illustrative of the patterns detected in other OECD countries.

Source: Swift, R. (2011), ‘The Relationship between Health and GDP in OECD Countries in the very Long Run’, Health Economics, 20, p. 310.

Source: Swift, R. (2011), ‘The Relationship between Health and GDP in OECD Countries in the very Long Run’, Health Economics, 20, p. 311.

Table 1 shows the relative changes of all three vari- ables (life expectancy, total GDP, and GDP per capita).

On average each 1% increase in life expectancy led to an increase in both GDP and GDP per capita of 40.1% and 12.6%, respectively, over the full period of estimation. However, when looking at only the 1921- 2001 period the figures change respectively to 30.4% and 14.6%. These results insist a possibly significant impact of health on GDP, but there exist many other factors that could have supported the rise in GDP and GDP per capita over this long-run period.

In examining the relationship between health and GDP, stationary testing of the variables was imple- mented, exercising Augmented Dickey-Fuller tests. All variables were put into log form (life expectancy, GDP, and GDP per capita), and consequently it was found that for all countries they were not station- ary; however, their initial differences were. For this reason the use of cointegration analysis to evaluate the interaction between the variables, given that the technique used permits for potential dual causality of the variables. Therefore, the Johansen multivariate cointegration model was selected so that both long run and short run approximations of the relationships between the variables, which are possibly endogenous, could be found.

Robin Swift concludes that improved health can positively impact economic growth via several chan- nels, which include the rise in total GDP, but more sig- nificantly, through long term increases in both human and physical capital that in turn stimulate productivity and GDP per capita. All 13 OECD countries tested in this paper presented long run cointegrating interactions between health and both total and per capita GDP. Re- sults show that a 1% increase in life expectancy led to an average 6% increase in total GDP and an on average 5% increase in GDP per capita. Moreover, total GDP and per capita GDP also has a substantial impact on life expectancy for most countries tested. These esti- mations recommend that developed countries continue policies promoting health, which in turn can continue to promote further economic growth, despite the fact that degenerative and non-communicable diseases are the primary health issues these countries face now, rather than infectious diseases that have contributed to significant gains in the past. Hence, this has clear implications for developing countries, which strive to mimic the growth path of the 13 OECD countries over the past two centuries, by stressing the importance of health related policies. Robin Swift acknowledges one of the limitations of his research being the usage of life expectancy as the only measure of health status. Bhargava et al. (2001) argues that using life expectancy as the sole measure of health status is a considerable drawback as it is an incomplete measure of society’s health, as it does not consider improvements such as nutrition, which can improve labour productivity.

DISEASE AND DEVELOPMENT: THE EFFECT OF LIFE EXPECTANCY ON ECONOMIC GROWTH – ACEMOGLU AND JOHNSON (2006)

Acemoglu and Johnson (2006) examine the ef- fect of life expectancy on economic growth using the international epidemiological transition period. This period was selected as an empirical strategy to isolate possibly exogenous variations in health states. Data for mortality by disease was collected from the League of Nations and national public health sources. These estimates were used to create an instrument for changes in life expectancy, referred in this paper as predicted mortality. The main results of this paper have been obtained using the two-stage least square estimation of the effect life expectancy has on both total and per capita GDP, all in log terms. While re- sults attained found no statistically significant impact of life expectancy on total GDP, a small positive ef- fect has been noted, which gradually increases over time. Moreover, countries with sizeable increases in life expectancy experienced some decline in their relative growth rates for per capita GDP. None of the estimations carried out showed any positive effects of life expectancy on GDP per capita during the 40-year horizon 1940-1980. Acemoglu and Johnston interpret their results using neoclassical growth theory. Hence, the first-order effect of a rise in life expectancy leads to an increase in population, in turn decreasing the capital to labour and land to labour ratios at first, consequently lowering income per capita. This initial fall in income per capita can be compensated through higher output as labour force participation increases. However, the benefits from a higher life expectancy level may not fully compensate the initial fall. Neoclassical growth theory also explains the smaller effect life expectancy has on GDP in the short run, in comparison to the long run, due to the fact that accumulation of capital is not instantaneous, but is a slow process. The above results indicate health does not have primary impact on economic growth. Despite their results they do not want to cross out health’s contribution to developing countries during the postwar period. Furthermore, they argue that global efforts can improve health statuses in less developed nations, without the need to involve long term costs in terms of per capita income, but are hesitant to agree completely with the notion that bad health conditions are the main cause of poverty in certain countries. The authors point out a drawback to their study by stating that the international epidemio- logical transition around the 1940s is not straightfor- wardly applicable to present times.

THE EFFECT OF HEALTH ON ECONOMIC GROWTH: A PRODUCTION FUNCTION APPROACH– BLOOM, CANNING, AND SEVILLA (2004)

Bloom et al. (2004) tried to establish the impact ofa population’s health on economic growth. They used a well-specified aggregate production that includes health in order to find the effect health has on labour productivity and approximate its strength. Moreover, the authors, knowing the multidimensional charac- teristic of human capital, incorporated all of its main components into the growth model to guarantee that they did not incorrectly overestimate the contribu- tion of one variable by falsely accrediting benefits of variables not used in the model. For example, this kind of estimation error can arise when examining the effect of health using life expectancy as its measure in nations with high life expectancy levels, since they usually have a labour force with more experience. Mincer (1974) states that experience has an influence on workers’ wages. Therefore, by including experi- ence in the growth model, they can avoid this potential bias in estimation. The inputs of the model include physical capital, labor, and human capital in the three dimensions of education, experience, and health. The model also considers the efficiency – total factor pro- ductivity (TFP) of these inputs. All the variables of the production function have been estimated using panel data for 1960-1990. Output data – GDP were acquired from the Penn World Tables, while life expectancy data was gathered from the United Nations (1998). The main result of their study proves that health has a positive and statistically-significant impact on eco- nomic growth. It estimates that on average a one-year improvement in the society’s life expectancy leads to a 4% rise in output. These findings clearly rationalize policies which increase expenditure on health invest- ments, as there is not only a direct impact of improved health on welfare, but also a relatively large effect on labour productivity. However, the model cannot differentiate between the effects of various types of health investments that affect specific groups within a society. Bloom, Canning and Sevilla admitted that increased life expectancy is able to increase output through not only labour productivity, but also via capital accumulation. In addition, only a fully specified growth model would be able to determine the growth rates and productivity of the inputs.

POLICY IMPLICATIONS

Robin Swift (2011) and Bloom et al. (2004) in their case studies prove that the causality running from health to income exists. Both studies highlight the importance of policies that promote health (e.g. increasing expenditure on health investments), which in turn will enhance economic growth. This special re- lationship creates a vicious circle where both variables stimulate each other leading to sustainable growth outcomes. On the other hand, Acemoglu and Johnson (2006) did not find any substantial evidence demon- stratinghealth’s positive impact on income. However, they stress that global efforts to improve health status in developing countries should still be of primary importance. These efforts can be carried out through policies, which do not involve long-term costs. Sala- i-Martin (2005) explains the detrimental effects if such policies are not enforced. In accordance with previous findings, health and income can stimulate each other, and hence, increased health enhances income, which then improves health and so on. However, this can run in the opposite direction where bad health low- ers income, which then decreases health further. This has been the issue for many African states in which the negative vicious circle leads to a so-called health- poverty trap. This kind of trap has drastic effects, as poverty cannot be fully eliminated without addressing critical health issues, which cannot be solved until poverty is removed. The final chapter will analyze the empirical evidence examined and try to solve the policy problems that governments face.

DISCUSSION AND CONCLUSIONS

Governments searching for policies directed to improve health first need to fully understand the pro- cesses and causality issue of the relationship between health and economic growth. For this reason policy- makers find it very difficult to imply any strategies, as the relationship is problematic, complicated, and contingent. The notion that “health is wealth” is still in its infancy, and continuously new studies arise, while the reversed causality “wealth is health” is a theory that has been acknowledged and backed by the majority of researchers, both theoretically and empirically. Suhrcke et al. (2005) states that current health policies are seen as interventions that attempt to increase health and delivery of health care as costs that need to be controlled, meaning that income remains the key variable and health consequences are only the finishing point of the “development” aims. However, literature presented in this paper sheds new light on the proposition that health does indeed play a key role in economic development and poverty reduction.

Over the past half-decade improvements in main health indicators have been outstanding. However, many countries still suffer from poor health and vari- ous diseases. Therefore, the UN’s eight Millennium Development Goals, which are targeted at developing countries, include a framework for reducing poverty and deprivation. Despite the causality from health to income not being fully acknowledged, health deter- mines both an individual’s physical (e.g. vigor, durabil- ity, and energy) and mental (e.g. intelligence, rational thinking) capabilities. Hence, since health is a basic determinant of human capital, increasing it should in turn improve the individual’s productivity. Following this line of thinking, productivity is positively corre- lated with income; therefore an increase in productivity should lead to higher income. Considering health as an influential part of human capital, it becomes a plausible variable that can affect economic growth. However, many previous studies (Schultz 1961, Mincer 1958) that examined the relationship between human capi- tal and economic productivity attributed most of the human capital progress to education. Schultz (1979), in his Nobel Prize lecture, underlined the importance of investing in health as it has a significant impact on production. The effect that health has on income can vary, depending upon the wealth of one country. Weil (2007) found that the biggest impact of health on GDP was in poor countries. Empirical evidence examining the impact of health on GDP in rich countries is mixed. For instance Rivera and Currais (2003) discovered increased health spending having a positive impact on productivity growth in OECD countries, contrary to Hartwig (2008) who proves no positive relationship between health and economic growth. These findings can be problematic to policymakers of developed countries. It is important to point out that one of the main problems that arises when determining the causality of health and income is endogeneity, which results from feedback effects or approximation errors, together with lack of attainability of an applicable date making the interpretation of causality very difficult.

Even though more and more researchers confirm that improvement of health and longevity spur economic growth and decrease poverty, the established view, which implies income affects health, is indisputable and still the prevailing one. Bloom and Canning (2001) argue that both directions of causality can work to- gether at the same time reinforcing one another. This leads to a virtuous circle where health enhancements stimulate economic growth, which then stimulates health.

The way in which governments will perceive the relationship between health and income has serious policy implications. For example, if the relationship were seen as running from income to health a natural policy strategy would involve projects to help the deprived, combat poverty, or reallocate income. On the other hand, if the direction of the relationship is reversed and is seen as running from health to income, policy consequences would include improvements in public health, such as retirement plans being structured and supported so that sick and elderly individuals do not become poor. Taking the causality from health to income into consideration as a viable relationship, governments still face the question of what policies to adopt in order to improve health and other social objectives. There are many different approaches scholars have suggested. Sachs (2004) recommends policies that involve increasing public health and social expenditures. Leipziger (2003) proposes a more multi-sectorial method, which includes putting stress on cross sector synergies, improvements in infrastructure and emphasis on the efficiency issue. On the other hand, Pritchett and Summers (1993) believe that policies with regard to improvements in health and social sector to be redundant, as economic growth is the main precursor of these outcomes. Hence, policies should be focused on enhancing income in general. Levine et al. (2004) argues that despite eco- nomic growth having a clear and undeniable positive influence on health, efforts to tackle specific health problems through improvements in accessibility of health care, pioneering new medicine, and encourage- ment of healthier lifestyles provide significant gains in the health status of countries. Furthermore, based on case studies of successful health related interventions, Levine et al. (2004) constructed a list of six features a public intervention should consist of:

I. Certain and sufficient funds from both domestic and international levels

II. Suitable political governance

III. A delivery system supported by technological innovation at a justifiable price

IV. A general technical agreement on the public health approach

V. Decent low level management

VI. Complete accessibility and effective use of information

It has been observed that under these specific ele- ments, public health interventions have effectively achieved their set goals even in the most underde- veloped countries facing extreme poverty and poor health systems. A good example of a successful public health intervention is one in Africa reducing measles incidents and deaths carried out by local governments with the support of the Measles Initiative partnership — led by the American Red Cross, United Nations Foundation, U.S. Centers for Disease Control and Prevention, UNICEF and World Health Organization. UNICEF (2007) published that from 2001 to 2006 the number of deaths recorded from measles in Africa fell by 75 % (from a projected 506,000 to 126,000). Chandra (2006) underlines the great importance of public health interventions, stating that the significant decrease in deaths from measles in Africa is not due to the improvement of individuals’ incomes, but instead is the result of both government and international sup- port to tackle this problem directly.

Concluding, evidence presented in this paper illu- minates the two-way relationship between economic growth and health. Bearing in mind the substantial influence of enhanced health to economic productiv- ity and growth, governments need to look at health expenses as an investment rather than a cost. Policy- makers should take a balanced approach, not over- regulating the market and always implementing a long run viewpoint. Political governance may be the key in constructing an environment where policies will guarantee that individuals’ health needs are satis- fied. Governments must take health seriously if they want sustain and improve upon economic and social outcomes.

BIBLIOGRAPHY:

1. Acemoglu, Daron, and Johnson, Simon (2006) ‘Disease and Development: The Effect of Life Expectancy on Economic Growth’, NBER Working Paper 12269.

2. Atun R.A. (2004) ‘What are the advantages and disadvantages of restructuring a health care system to be more focused on primary care services?’, World Health Organisation Health Evidence Network, WHO Regional Office for Europe, Copenhagen.